• Design & Manufacturing
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• 제17권1호
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• pp.20-26
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• 2023

Lab-on-a-disc is a circular disc shape of cartridge that can be used for blood-based liquid biopsy to diagnose an early stage of cancer. Currently, liquid biopsies are regarded as a time-consuming process, and require sophisticated skills to precisely separate cell-free DNA (cfDNA) and circulating tumor cells (CTCs) floating in the bloodstream for accurate diagnosis. However, by applying the lab-on-a-disc to liquid biopsy, the entire process can be operated automatically. To do so, the lab-on-a-disc should be designed to prevent blood leakage during the centrifugation, transport, and dilution of blood inside the lab-on-a-disc in the process of liquid biopsy. In this study, the main components of lab-on-a-disc for liquid biopsy are fabricated by injection molding for mass production, and ultrasonic welding is employed to ensure the bonding strength between the components. To guarantee accurate ultrasonic welding, the flatness of the components is optimized numerically by using the response surface methodology with four main injection molding processing parameters, including the mold & resin temperatures, the injection speed, and the packing pressure. The 27 times finite element analyses using Moldflow® reveal that the injection time and the packing pressure are the critical factors affecting the flatness of the components with an optimal set of values for all four processing parameters. To further improve the flatness of the lab-on-a-disc components for stable mass production, a quarter-disc shape of lab-on-a-disc with a radius of 75 mm is used instead of a full circular shape of the disc, and this significantly decreases the standard deviation of flatness to 30% due to the reduced overall length of the injection molded components by one-half. Moreover, it is also beneficial to use a quarter disc shape to manage the deviation of flatness under 3 sigma limits.

• 산업경영시스템학회지
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• 제44권4호
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• pp.65-75
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• 2021

This study explores multiple variables of an OTT service for discovering hidden relationship between rating and the other variables of each successful and failed content, respectively. In order to extract key variables that are strongly correlated to the rating across the contents, this work analyzes 170 Netflix original dramas and 419 movies. These contents are classified as success and failure by using the rating site IMDb, respectively. The correlation between the contents, which are classified via rating, and variables such as violence, lewdness and running time are analyzed to determine whether a certain variable appears or not in each successful and failure content. This study employs a regression analysis to discover correlations across the variables as a main analysis method. Since the correlation between independent variables should be low, check multicollinearity and select the variable. Cook's distance is used to detect and remove outliers. To improve the accuracy of the model, a variable selection based on AIC(Akaike Information Criterion) is performed. Finally, the basic assumptions of regression analysis are identified by residual diagnosis and Dubin Watson test. According to the whole analysis process, it is concluded that the more director awards exist and the less immatatable tend to be successful in movies. On the contrary, lower fear tend to be failure in movies. In case of dramas, there are close correlations between failure dramas and lower violence, higher fear, higher drugs.

• 정신신체의학
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• 제12권2호
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• pp.103-121
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• 2004

감각 및 운동 이상 증상을 동반하면서 꾀병이 의심되는 환자를 가려내는 방법에 대해서 약술하고 몇 개의 증례를 예시하였다. 꾀병을 규명하기 위해서는 우선 전환 장애, 가장성 장애를 차례로 증명하여 제외시켜야 한다. 이를 위한 방법으로는 자세한 병력 수집과 조사, 면밀한 신경학적 검사, 심리검사, 장시간의 면담 그리고 광범위한 행동 관찰이 필요하다. 그러나 증상 형성의 동기나 의도의 본질을 파악하기란 어려워서 환자의 고백에 의해 알게되는 경우도 있다. 신경 심리검사를 포함한 임상심리 검사를 통하여 꾀병의 가능성을 가려내고, 질병행동 특성을 파악하거나 기계적인 측정도구를 이용하기도 한다. 그러나 아직 객관적으로 타당한 검사 방법은 부족하다. 최근, 통증 차단제를 이용한 진성(眞性) 통증 구별법은 객관적인 검사법의 하나이다. 사고나 보상 문제가 겹친 만성 통증 환자는 꾀병의 가능성이 엿보인다 하더라도 많은 수에서 시간 경과와 환경의 영향으로 인해서 정신사회적 합병증을 동반한다. 향후 임상 심리검사법이 발달되고 행동과 의도성에 관한 뇌 기능의 연구론 통해 신체 증상이나 행위의 진실성에 대한 구별력은 더욱 향상될 것이다.

• 공업화학
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• 제16권5호
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• pp.620-627
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• 2005

본 연구에서는 골판지포장재에 대하여 LCA를 수행하고 그 결과를 바탕으로 생산공정의 환경성 개선을 수행하였다. 연구범위는 원료취득단계에서부터 원단제조단계, 상자제조단계까지로 구분하여 각 단계 및 세부공정별로 LCA에 의한 환경영향을 평가하였다. 영향범주는 자원고갈, 지구온난화, 오존층고갈, 광화학산화물생성, 산성화, 부영양화, 생태독성, 인간독성의 8가지 범주로 구분하여 평가하였다. 평가결과, 전체 환경영향 중 원료취득단계에서 발생하는 영향이 약 92%로 가장 높게 차지하는 것으로 나타났으며 라이너지 제조공정에서 가장 큰 환경영향이 있는 것으로 나타났다. 원단제조단계와 상자제조단계의 공정에서 발생하는 환경영향은 원단제조단계의 주 공정인 single facer 및 D/W backer 공정에서 가장 높은 영향을 가지는 것으로 나타났다. 이와 같이 환경영향이 나타나는 주요 원인은 전력, 중유 등의 에너지인 것으로 나타났다. 또한, 포장재의 청정생산공정구축을 위하여 생산공정에 대한 진단을 수행하였다. 진단을 통하여 손모율 저감과 상자의 내압강도에 대한 개선효과를 평가하였으며, 개선 후 환경영향은 개선 전보다 약 3.8% 환경영향이 저감된 것으로 나타났다.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.886-889
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• 2017

An active Fault Tolerant Model Predictive Control (FTMPC) using Fuzzy scheduler is developed. Fault tolerant Control (FTC) system stages are broadly classified into two namely Fault Detection and Isolation (FDI) and fault accommodation. Basically, the faults are identified by means of state estimation techniques. Then using the decision based approach it is isolated. This is usually performed using soft computing techniques. Fuzzy Decision Making (FDM) system classifies the faults. After identification and classification of the faults, the model is selected by using the information obtained from FDI. Then this model is fed into FTC in the form of MPC scheme by Takagi-Sugeno Fuzzy scheduler. The Fault tolerance is performed by switching the appropriate model for each identified faults. Thus by incorporating the fuzzy scheduled based FTC it becomes more efficient. The system will be thereafter able to detect the faults, isolate it and also able to accommodate the faults in the sensors and actuators of the Continuous Stirred Tank Reactor (CSTR) process while the conventional MPC does not have the ability to perform it.

• 한국멀티미디어학회논문지
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• 제17권1호
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• pp.1-7
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• 2014

Hippocampus is an important part of brain which is related with early memory storage and spatial navigation. By observing the anatomy of hippocampus, some brain diseases effecting human memory (e.g. Alzheimer, schizophrenia, etc.) can be diagnosed and predicted earlier. The diagnosis process is highly related with hippocampus segmentation. In this paper, hippocampus segmentation using Active Shape Model, which not only works based on image intensity, but also by using prior knowledge of hippocampus shape and intensity from the training images, is proposed. The results show that ASM is applicable in segmenting hippocampus from whole brain MR image. It also shows that adding more images in the training set results in better accuracy of hippocampus segmentation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2192-2197
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• 2005

This paper describes how to diagnose SBR plant equipment using time-series data mining. It shows the equipment diagnostics based upon vibration signals that are acquired from each device for process control. Data transform techniques including two data preprocessing skills and data mining methods were employed in the data analysis. The proposed method is not only suitable for SBR equipment, but is also suitable for other industrial devices. The experimental results performed on a lab-scale SBR plant show a good equipment-management performance.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.119-124
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• 1994

Morden industrial society pursues unmanned system and automation of manufacturing rocess. Abreast with this tendensy, prodution of goods which requires advaned accuracy is increasing as well. According to this, the work sensing time of dressing by monitoring and diagnosis the condition of grinding, which is the representative way in accurate manufacturing, is a important work to prevent serios damages which affect grinding process or products by wearing wheel. Computer vision system is composed, so that grind wheel wurface was acquired by CCD camera and the change of cutting is composed. Then we used autometic threshoding technique from histogram as a way of deviding cutting edge which is used in manufacturing from the other parts. As a result, we are trying to approach unmanned system and sutomation by deciding more accurate time of dressing and by visualizing behavior of grinding wheel by marking use of computer vision.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.563-564
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• 2006

A single photon counting type image sensor which is applicable for medical diagnosis with digitally obtained image and industrial purpose has been designed using $0.25{\mu}m$triple well CMOS process.

• 한국안전학회지
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• 제20권3호
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• pp.19-26
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• 2005

There are three reasoning method in fault diagnosis process. The shallow reasoning is based on the experiential knowledge and deep reasoning is based on physical model. Hybrid reasoning is mixing two type reasoning. This study describes about fault train embodiment of screw type air compressor that is used widely in industrial facilities by using various experimental method and shallow reasoning. We investigate macroscopic failure cause of air compressor through naked eye observation and then microscopic failure cause by various experimental method. We composed fault train with fault knowledge based on empirical data and scientific data that is acquired through several experiments. It is possible to analysis system reliability and failure rate with these fault train.